Innovative electrochemical biosensor for toxicological investigations on algae and cyanobacteria

Recent advances in electrochemical cell-based biosensors for food analysis: Strategies for sensor construction

Owing to their advantages such as great specificity, sensitivity, rapidity, and possibility of noninvasive and real-time monitoring, electrochemical cell-based biosensors (ECBBs) have been a powerful tool for food analysis encompassing the areas of nutrition, flavor, and safety. Notably, the distinctive biological relevance of ECBBs enables them to mimic physiological environments and reflect cellular behaviors, leading to valuable insights into the biological function of target components in food. Compared with previous reviews, this review fills the current gap in the narrative of ECBB construction strategies. The review commences by providing an overview of the materials and configuration of ECBBs, including cell types, cell immobilization strategies, electrode modification materials, and electrochemical sensing types. Subsequently, a detailed discussion is presented on the fabrication strategies of ECBBs in food analysis applications, which are categorized based on distinct signal sources. Lastly, we summarize the merits, drawbacks, and application scope of these diverse strategies, and discuss the current challenges and future perspectives of ECBBs. Consequently, this review provides guidance for the design of ECBBs with specific functions and promotes the application of ECBBs in food analysis.

2-Hydroxy-1,4-Naphthoquinone: A Promising Redox Mediator for Minimizing Dissolved Organic Nitrogen and Eutrophication Effects of Wastewater Effluent

Researchers and engineers are committed to finding effective approaches to reduce dissolved organic nitrogen (DON) to meet more stringent effluent total nitrogen limits and minimize effluent eutrophication potential. Here, we provided a promising approach by adding specific doses of 2-hydroxy-1,4-naphthoquinone (HNQ) to postdenitrification bioreactors. This approach of adding a small dosage of 0.03-0.1 mM HNQ effectively reduced the concentrations of DON in the effluent (ANOVA, p < 0.05) by up to 63% reduction of effluent DON with a dosing of 0.1 mM HNQ when compared to the control bioreactors. Notably, an algal bioassay indicated that DON played a dominant role in stimulating phytoplankton growth, thus effluent eutrophication potential in bioreactors using 0.1 mM HNQ dramatically decreased compared to that in control bioreactors. The microbe-DON correlation analysis showed that HNQ dosing modified the microbial community composition to both weaken the production and promote the uptake of labile DON, thus minimizing the effluent DON concentration. The toxic assessment demonstrated the ecological safety of the effluent from the bioreactors using the strategy of HNQ addition. Overall, HNQ is a promising redox mediator to reduce the effluent DON concentration with the purpose of meeting low effluent total nitrogen levels and remarkably minimizing effluent eutrophication effects.

Current status and prospects of algal bloom early warning technologies: A Review

In recent years, frequent occurrences of algal blooms due to environmental changes have posed significant threats to the environment and human health. This paper analyzes the reasons of algal bloom from the perspective of environmental factors such as nutrients, temperature, light, hydrodynamics factors and others. Various commonly used algal bloom monitoring methods are discussed, including traditional field monitoring methods, remote sensing techniques, molecular biology-based monitoring techniques, and sensor-based real-time monitoring techniques. The advantages and limitations of each method are summarized. Existing algal bloom prediction models, including traditional models and machine learning (ML) models, are introduced. Support Vector Machine (SVM), deep learning (DL), and other ML models are discussed in detail, along with their strengths and weaknesses. Finally, this paper provides an outlook on the future development of algal bloom warning techniques, proposing to combine various monitoring methods and prediction models to establish a multi-level and multi-perspective algal bloom monitoring system, further improving the accuracy and timeliness of early warning, and providing more effective safeguards for environmental protection and human health.

Understanding the Risks of Diffusion of Cyanobacteria Toxins in Rivers, Lakes, and Potable Water

Blue-green algae, or cyanobacteria, may be prevalent in our rivers and tap water. These minuscule bacteria can grow swiftly and form blooms in warm, nutrient-rich water. Toxins produced by cyanobacteria can pollute rivers and streams and harm the liver and nervous system in humans. This review highlights the properties of 25 toxin types produced by 12 different cyanobacteria genera. The review also covered strategies for reducing and controlling cyanobacteria issues. These include using physical or chemical treatments, cutting back on fertilizer input, algal lawn scrubbers, and antagonistic microorganisms for biocontrol. Micro-, nano- and ultrafiltration techniques could be used for the removal of internal and extracellular cyanotoxins, in addition to powdered or granular activated carbon, ozonation, sedimentation, ultraviolet radiation, potassium permanganate, free chlorine, and pre-treatment oxidation techniques. The efficiency of treatment techniques for removing intracellular and extracellular cyanotoxins is also demonstrated. These approaches aim to lessen the risks of cyanobacterial blooms and associated toxins. Effective management of cyanobacteria in water systems depends on early detection and quick action. Cyanobacteria cells and their toxins can be detected using microscopy, molecular methods, chromatography, and spectroscopy. Understanding the causes of blooms and the many ways for their detection and elimination will help the management of this crucial environmental issue.